文章基本信息

标题：Parameters Optimization of Least Squares Support Vector Machines and Its Application
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作者：Xie, Chunli ; Shao, Cheng ; Zhao, Dandan 等
期刊名称：Journal of Computers
印刷版ISSN：1796-203X
出版年度：2011
卷号：6
期号：9
页码：1935-1941
DOI：10.4304/jcp.6.9.1935-1941
语种：English
出版社：Academy Publisher
摘要：Parameters optimization plays an important role for the performance of least squares support vector machines (LS-SVM). In this paper, a novel parameters optimization method for LS-SVM is presented based on chaotic ant swarm (CAS) algorithm. Using this method, the optimization model is established, within which the fitness function is the mean square error (MSE) index, and the constraints are the ranges of the designing parameters. After having been validated its effectiveness by an artificial data experiment, the proposed method is then used in the identification for inverse model of the nonlinear under-actuated systems. Finally real data simulation results are given to show the efficiency.
关键词：Least Squares Support Vector Machines; Parameters Optimization; Chaotic Ant Swarm Algorithm